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In this article:

    General description

    Learning environments

    Within the Mail.Ru Cloud Solutions platform, you can create a data scientists workspace.

    The data scientist workspace is a virtual machine image that includes popular machine learning frameworks and tools.

    Composition of the product

    CS a: Ubuntu 18.04 "Machine Learning"

    Pre-installed components:

    • NVIDIA GPU drivers
    • NVIDIA CUDA
    • NVIDIA CUDA Deep Neural Network Librayr (cuDNN)
    • NVIDIA Docker
    • Anaconda Batch Manager
    • C / C ++ development tools (gcc, g ++, clang, gdb, make, cmake, etc.)
    • Version control systems (git, svn, mercurial)

    Working with conda

    Conda is a cross-platform package manager for Python, R, Ruby, Lua, Scala, Java, JavaScript, C / C ++, FORTRAN. Conda is an advanced counterpart to pip + virtualenv.

    The conda repos contain all the popular machine learning tools and frameworks such as pandas , scikit-learn , Matplotlib , XGBoost , LightGBM , PyTorch , TensorFlow, and more.

    Vision

    Vision is a technology for recognizing faces, objects, processes based on machine learning and artificial neural networks. Vision will automate and improve the accuracy of complex visual inspection of varying complexity.

    • 98% accuracy of face detection among a million
    • TensorRT on inference, <10ms on photo on GPU
    • 314 scene recognition classes, 25,000 object classes

    Vision technologies are available through APIs that are constantly evolving. A list of them is available in this help center. Using the API, you can solve such cases as:

    • Definition of scenes and objects
    • Tracking people
    • Celebrity recognition
    • Recognizing text in images
    • Vehicle detection
    • Increase resolution
    • Search for attractions
    • Identification of a manufacturing defect
    • Determination of car numbers
    • Image moderation

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